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Grapes are prone to various diseases throughout their growth cycle, and the failure to promptly control these diseases can result in reduced production and even complete crop failure. Therefore, effective disease control is essential for maximizing grape yield. Accurate disease identification plays a crucial role in this process. In this paper, we proposed a real-time and lightweight detection model called Fusion Transformer YOLO for 4 grape diseases detection. The primary source of the dataset comprises RGB images acquired from plantations situated in North China. Firstly, we introduce a lightweight high-performance VoVNet, which utilizes ghost convolutions and learnable downsampling layer. This backbone is further improved by integrating effective squeeze and excitation blocks and residual connections to the OSA module. These enhancements contribute to improved detection accuracy while maintaining a lightweight network. Secondly, an improved dual-flow PAN+FPN structure with Real-time Transformer is adopted in the neck component, by incorporating 2D position embedding and a single-scale Transformer Encoder into the last feature map. This modification enables real-time performance and improved accuracy in detecting small targets. Finally, we adopt the Decoupled Head based on the improved Task Aligned Predictor in the head component, which balances accuracy and speed. Experimental results demonstrate that FTR-YOLO achieves the high performance across various evaluation metrics, with a mean Average Precision (mAP) of 90.67%, a Frames Per Second (FPS) of 44, and a parameter size of 24.5M. The FTR-YOLO presented in this paper provides a real-time and lightweight solution for the detection of grape diseases. This model effectively assists farmers in detecting grape diseases.

To tackle the high resource consumption in occluded person re-identification, sparse attention mechanisms based on Vision Transformers (ViTs) have become popular. However, they often suffer from performance degradation with long sequences, omission of crucial information, and token representation convergence. To address these issues, we introduce AIRHF-Net: an Adaptive Interaction Representation Hierarchical Fusion Network, named AIRHF-Net, designed to enhance pedestrian identity recognition in occluded scenarios. Our approach begins with the development of an Adaptive Local-Window Interaction Encoder (AL-WIE), which aims to overcome the inherent subjective limitations of traditional sparse attention mechanisms. This innovative encoder merges window attention, adaptive local attention, and interaction attention, facilitating automatic localization and focusing on visible pedestrian regions within images. It effectively extracts contextual information from window-level features while minimizing the impact of occlusion noise. Additionally, recognizing that ViTs may lose spatial information in deeper structural layers, we implement a Local Hierarchical Encoder (LHE). This component segments the input sequence in the spatial dimension, integrating features from various spatial positions to construct hierarchical local representations that substantially enhance feature discriminability. To further augment the quality and breadth of datasets, we adopt an Occlusion Data Augmentation Strategy (ODAS), which bolsters the model’s capacity to extract critical information under occluded conditions. Extensive experiments demonstrate that our method achieves improved performance on the Occluded-DukeMTMC dataset, with a rank-1 accuracy of 69.6% and an mAP of 61.6%.

Accurate identification of coffee fruit maturity is critical for optimizing harvest timing and ensuring bean quality, but manual inspection is time-consuming and prone to subjectivity. Automated visual detection faces challenges including subtle color differences among maturity stages, frequent occlusions within fruit clusters, variable lighting, and abundant small-scale targets. In this paper, we propose SSViT-YOLOv11, an improved YOLOv11n-based framework that integrates Single Scale Vision Transformer (SSViT) into the backbone and refines multi-scale feature fusion to enhance context modeling and small-object representation. The C3K2 modules in YOLOv11n are integrated with Arbitrary Kernel Convolution (AKConv) and multi-scale convolutional attention (MSCA) is added in the head, effectively improving detection accuracy and rendering the model more lightweight. Experimental results show that SSViT-YOLOv11 achieves superior performance across multiple evaluation metrics. Specifically, the model attains a precision of 81.1%, a recall of 77.4%, and a mean Average Precision (mAP@50) of 84.54%, while operating at 23 FPS and requiring only 2.16 million parameters. These results indicate that the proposed model offers a favorable balance of accuracy, inference speed, and model compactness, making it well suited for assisting farmers in coffee fruit maturity assessment.

There are various indoor fingerprint localization techniques utilizing the similarity of received signal strength (RSS) to discriminate the similarity of positions. However, due to the varied states of different wireless access points (APs), each AP’s contribution to RSS similarity varies, which affects the accuracy of localization. In our study, we analyzed several critical causes that affect APs’ contribution, including APs’ health states and APs’ positions. Inspired by these insights, for a large-scale indoor space with ubiquitous APs, a threshold was set for all sample RSS to eliminate the abnormal APs dynamically, a correction quantity for each RSS was provided by the distance between the AP and the sample position to emphasize closer APs, and a priority weight was designed by RSS differences (RSSD) to further optimize the capability of fingerprint distances (FDs, the Euclidean distance of RSS) to discriminate physical distance (PDs, the Euclidean distance of positions). Integrating the above policies for the classical WKNN algorithm, a new indoor fingerprint localization technique is redefined, referred to as FDs’ discrimination capability improvement WKNN (FDDC-WKNN). Our simulation results showed that the correlation and consistency between FDs and PDs are well improved, with the strong correlation increasing from 0 to 76% and the high consistency increasing from 26% to 99%, which confirms that the proposed policies can greatly enhance the discrimination capabilities of RSS similarity. We also found that abnormal APs can cause significant impact on FDs discrimination capability. Further, by implementing the FDDC-WKNN algorithm in experiments, we obtained the optimal K value in both the simulation scene and real library scene, under which the mean errors have been reduced from 2.2732 m to 1.2290 m and from 4.0489 m to 2.4320 m, respectively. In addition, compared to not using the FDDC-WKNN, the cumulative distribution function (CDF) of the localization errors curve converged faster and the error fluctuation was smaller, which demonstrates the FDDC-WKNN having stronger robustness and more stable localization performance.

Lanthanide‐based NIR‐II‐emitting materials (1000–1700 nm) show promise for optoelectronic devices, phototherapy, and bioimaging. However, one major bottleneck to prevent their widespread use lies in low quantum efficiencies, which are significantly constrained by various quenching effects. Here, a highly oriented (222) facet is achieved via facet engineering for Cs2NaErCl6 double perovskites, enabling near‐complete suppression of NIR‐II luminescence quenching. The optimally (222)‐oriented Cs2Ag0.10Na0.90ErCl6 microcrystals emit Er3+ 1540 nm light with unprecedented high quantum efficiencies of 90 ± 6% under 379 nm UV excitation (ultralarge Stokes shift >1000 nm), and a record near‐unity quantum yield of 98.6% is also obtained for (222)‐based Cs2NaYb0.40Er0.60Cl6 microcrystallites under 980 nm excitation. With combined experimental and theoretical studies, the underlying mechanism of facet‐dependent Er3+ 1540 nm emissions is revealed, which can contribute to surface asymmetry‐induced breakdown of parity‐forbidden transition and suppression of undesired non‐radiative processes. Further, the role of surface quenching is reexamined by molecular dynamics based on two facets, highlighting the drastic two‐phonon coupling effect of a hydroxyl group to 4I13/2 level of Er3+. Surface‐functionalized facets will provide new insights for tunable luminescence in double perovskites, and open up a new avenue for developing highly efficient NIR‐II emitters toward broad applications. The preferred (222) facet in Cs2NaErCl6 double perovskite is favorable for Er3+ 1540 nm emission with a record quantum yield of 98.6% under 980 nm excitation, which is useful for surface modification. These findings suggest facet engineering is a new way for realizing highly efficient Er3+‐based NIR‐II emitters toward broad applications.

Low‐dimensional halide perovskites are highly susceptible to thermal quenching (TQ) due to strong soft lattice nature. Currently, examples of thermally enhanced NIR luminescence in low‐dimensional materials are very scarce to the knowledge. Herein, the active role of vibronic coupling is manifested through thermal tunability of broadband NIR emission in 0D W4+‐activated Cs2ZrCl6, leading to anti‐TQ behavior ranging from 80 to 613 K. Interestingly, the internal quantum efficiency is dramatically boosted from 55.9% to 92.9% in Cs2ZrCl6: W4+, Ce4+ while retaining zero‐TQ luminescence between 303 and 423 K. Transient‐state spectroscopy reveal the distribution of thermally released charge carriers among the vibronically coupled d‐electronic states of W4+ ion is responsible for excellent thermal stability. Density functional theory calculations confirm that weak transient lattice distortion of isolated [WCl6]2– octahedra in the excited state can combat TQ enabled by Franck–Condon vibronic coupling. Utilizing this thermal‐tolerant characteristic, both bandwidth‐ and lifetime‐based thermometers have been developed with low temperature uncertainties below 0.12 K. Moreover, NIR spectroscopy‐type sensor is presented for quantitative HF gas detection with concentration‐ and temperature‐dependent high sensing response and low detection limit. These findings may provide a vital insight into vibronic coupling‐assisted heat‐favorable NIR emissions in low‐dimensional materials for versatile applications. A vibronic coupling‐assisted way is provided for circumventing thermal quenching related to transient lattice distortion in 0D halide perovskites, and this study offers comprehending electron–lattice interactions in low‐dimensional host–W4+ dopant systems for the development of thermally tunable NIR spectroscopy applications, such as HF gas sensing and thermometry.

As the main source of extracellular matrix proteins in tumor stroma, hepatic stellate cells (HSCs) have a great impact on biological behaviors of hepatocellular carcinoma (HCC). In the present study, we have investigated a mechanism whereby HSCs modulate the chemoresistance of hepatoma cells. We used human HSC line lx-2 and chemotherapeutic agent cisplatin to investigate their effects on human HCC cell line Hep3B. The results showed that cisplatin resistance in Hep3B cells was enhanced with LX-2 CM (cultured medium) exposure in vitro as well as co-injection with LX-2 cells in null mice. Meanwhile, in presence of LX-2 CM, Hep3B cells underwent epithelial to mesenchymal transition (EMT) and upregulation of cancer stem cell (CSC) -like properties. Besides, LX-2 cells synthesized and secreted hepatic growth factor (HGF) into the CM. HGF receptor tyrosine kinase mesenchymal-epithelial transition factor (Met) was activated in Hep3B cells after LX-2 CM exposure. The HGF level of LX-2 CM could be effectively reduced by using HGF neutralizing antibody. Furthermore, depletion of HGF in LX-2 CM abolished its effects on activation of Met as well as promotion of the EMT, CSC-like features and cisplatin resistance in Hep3B cells. Collectively, secreting HGF into tumor milieu, HSCs may decrease hepatoma cells sensitization to chemotherapeutic agents by promoting EMT and CSC-like features via HGF/Met signaling.

In China, hepatitis E virus (HEV) is prevalent and causes disease, but its epidemiological profile is not well understood. We used a commercial enzyme-linked immunosorbent assay to detect total antibodies to hepatitis E virus in 15,862 serum samples collected during the Third National Viral Hepatitis Prevalence Survey. The results were analyzed to calculate estimates of HEV seroprevalence and to examine the effects of some putative risk factors. The seroprevalence of HEV in the general Chinese population during the period from 2005 through 2006 was 23.46% (95% confidence interval [CI], 18.41%-28.50%). The farming population, the age group of 15-60 year olds, and those living in the Midwest or Mideast region and in Xinjiang province had the highest seroprevalence estimates. The prevalence of HEV is high in China. The seroprevalence rate of HEV shows an unbalanced distribution among areas with different geographic location and economic development levels. The characteristics of the distribution associated may be due to the route of HEV transmission (via contaminated water or animal reservoirs). Within the same region, the seroprevalence of HEV is generally increased with age.

In 2011, a study on preventing mother-to-child transmission (PMTCT) of Hepatitis B virus (HBV) was conducted in Yunan province, China, and a child cohort was formed to assess PMTCT's long-term effectiveness. In 2022, subjects were randomly selected from this cohort to investigate HBV infection status and anti-HBs antibody levels among the HBsAg-negative children from the 2011 PMTCT group. HBV markers (HBsAg, anti-HBs, anti-HBc) and genomic information were detected, and risk factors for HBV breakthrough infection were analyzed. In total, 235 children were enrolled. HBsAg and anti-HBc positive rates were 1.7 % (4/235) and 5.96 % (14/235). HBsAg prevalence did not substantially increase, but four new HBV carriers were identified, with S gene sequences highly homologous to their parents'. The anti-HBs positive rate dropped significantly (from 86.38 % in 2011 to 58.30 % in 2022, χ2 = 46.32, P < 0.001), yet it went up among those who had booster vaccinations (93.2 % in 2022; 78.0 % in 2011), though antibody levels did not increase. Phylogenetic analysis confirmed the possible intrafamilial HBV transmission and no significant important mutations. Univariate and logistic regression analyses indicated that maternal HBeAg positivity were a major risk factors for children's HBV breakthrough infection (OR = 4.23, 95 % CI: 1.17–15.25). In conclusion, the positive rate and levels of anti-HBs antibodies have declined over time, but infection rates has not substantially increased. Children of HBsAg-positive parents remained at high risk of HBV breakthrough infection. Even with successful PMTCT, measures should be taken to maintain their immunity and reduce direct HBV exposure. •Eleven years after the birth, infants born to HBsAg-positive mothers had HBsAg and anti-HBc positivity rates of 1.70 % and 5.96 %, respectively, with no significant increase in HBsAg prevalence.•The positivity rate and titers of anti-HBs antibodies decreased over time, but positivity rate increased among those received booster vaccinations.•Evidence of intrafamilial transmission was observed, with no significant key mutations detected, and maternal HBeAg positivity identifying as a significant risk factor.

Low‐dimensional halide perovskites are highly susceptible to thermal quenching (TQ) due to strong soft lattice nature. Currently, examples of thermally enhanced NIR luminescence in low‐dimensional materials are very scarce to the knowledge. Herein, the active role of vibronic coupling is manifested through thermal tunability of broadband NIR emission in 0D W 4+ ‐activated Cs 2 ZrCl 6 , leading to anti‐TQ behavior ranging from 80 to 613 K. Interestingly, the internal quantum efficiency is dramatically boosted from 55.9% to 92.9% in Cs 2 ZrCl 6 : W 4+ , Ce 4+ while retaining zero‐TQ luminescence between 303 and 423 K. Transient‐state spectroscopy reveal the distribution of thermally released charge carriers among the vibronically coupled d ‐electronic states of W 4+ ion is responsible for excellent thermal stability. Density functional theory calculations confirm that weak transient lattice distortion of isolated [WCl 6 ] 2– octahedra in the excited state can combat TQ enabled by Franck–Condon vibronic coupling. Utilizing this thermal‐tolerant characteristic, both bandwidth‐ and lifetime‐based thermometers have been developed with low temperature uncertainties below 0.12 K. Moreover, NIR spectroscopy‐type sensor is presented for quantitative HF gas detection with concentration‐ and temperature‐dependent high sensing response and low detection limit. These findings may provide a vital insight into vibronic coupling‐assisted heat‐favorable NIR emissions in low‐dimensional materials for versatile applications.